In image processing contexts, particularly in low light conditions, spatial noise reduction may not accurately reduce noise as there is difficulty in distinguishing detail and noise. The use of strong spatial noise reduction (SPNR) may result in either a blurry image with a loss of detail or a noisy image. In such conditions, temporal noise reduction (TNR) may provide higher image and/or video quality.
However, temporal noise reduction techniques may have difficulties reducing noise for fast moving objects and/or for occluded regions (e.g., image regions that were obstructed in a previous image and revealed in a current image). Such fast moving objects and/or occluded regions may not have good matches in the reference image, providing difficulty in applying temporal noise reduction.
It may be advantageous to perform improved temporal noise reduction for images, which may improve image quality by reducing noise in static regions (e.g., those image regions that are not changing in the current image with respect to previous image(s)), moving regions (e.g., those image regions that are moving in the current image with respect to previous image(s)), and occluded regions (e.g., image regions that were obstructed in a previous image and revealed in a current image) without sacrificing detail level. It is with respect to these and other considerations that the present improvements have been needed. Such improvements may become critical as the desire to attain high quality images becomes more widespread.